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Shahar Yadin

2 accepted papers

2024

Classification Diffusion Models: Revitalizing Density Ratio Estimation

NeurIPS 2024poster

A prominent family of methods for learning data distributions relies on density ratio estimation (DRE), where a model is trained to *classify* between data samples and samples from some reference distribution. DRE-based models can directly output the likelihood for any given input, a highly desired…

Cited by 1SourcePDFScholar
2023

SinDDM: A Single Image Denoising Diffusion Model

ICML 2023poster

Denoising diffusion models (DDMs) have led to staggering performance leaps in image generation, editing and restoration. However, existing DDMs use very large datasets for training. Here, we introduce a framework for training a DDM on a single image. Our method, which we coin SinDDM, learns the inte…